Verified:GitHub

maira-main-agent

Orchestrate multi-agent research workflows for reports and literature surveys.

2|Updated Jan 25, 2026

Search Tags:#report generation #AI orchestration #RAG #multi-agent #literature review #research assistant #GitHub analysis

Ready to run

npx skills add https://github.com/Bhuvansai-16/MAIRA --skill maira-main-agent

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: maira-main-agent
Source: https://github.com/Bhuvansai-16/MAIRA/tree/main/backend/skills/main-agent
Command: npx skills add https://github.com/Bhuvansai-16/MAIRA --skill maira-main-agent

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill acts as the central orchestrator for complex research tasks, streamlining multi-agent workflows to produce professional reports and literature reviews.

Core Features & Use Cases

Intelligent Triage: Automatically detects user intent (chat, deep research, literature survey) and selects the appropriate workflow.
Multi-Agent Coordination: Manages up to 8 specialized subagents for tasks like web searching, drafting, verification, and report generation.
RAG Integration: Prioritizes uploaded documents for research and analysis.
GitHub Analysis: Integrates GitHub repository analysis into research workflows.
Use Case: Request a comprehensive literature review on a specific scientific topic, and the agent will coordinate specialized agents to find papers, synthesize findings, and generate a downloadable PDF report.

Quick Start

Use the maira-main-agent skill to perform a deep research task on the impact of AI in healthcare.

Frequently Asked Questions about maira-main-agent

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate literature review and report generation using multi-agent workflows?▼

Multi-agent report generation orchestrates specialized subagents to search, synthesize, and format findings. This skill coordinates up to eight agents to automate literature surveys and produce professional downloadable research reports.

How does RAG integration work with uploaded documents for research analysis?▼

RAG integration prioritizes your uploaded documents to ground research analysis. The orchestrator uses retrieval-augmented generation to extract context from local files, ensuring literature surveys and reports reference your specific source material.

Can I use GitHub repository analysis within a deep research workflow?▼

Yes, GitHub analysis integrates directly into deep research workflows. The orchestrator coordinates subagents to analyze repository content alongside web searches and uploaded documents, synthesizing code and documentation into comprehensive reports.

What is the best way to coordinate multiple subagents for deep analysis and verification?▼

Multi-agent coordination uses tier-based decision logic to route tasks to specialized subagents. This skill manages up to eight agents for web searching, drafting, and verification loops, ensuring deep analysis undergoes rigorous fact-checking before report generation.

Does this research assistant require any specific dependencies to run?▼

No external dependencies are required to run this research assistant. The skill operates through internal scripts to manage mode detection, subagent coordination, and direct tool usage for web searches and document exports.

When should I not use an AI orchestration workflow for literature surveys?▼

AI orchestration workflows for literature surveys are not ideal for simple factual lookups. The multi-agent coordination and verification loops are designed for deep analysis and comprehensive reviews, adding unnecessary overhead to basic chat interactions.